Hemodynamic analysis of vessels using recurrent neural network
A technology of hemodynamics and blood vessels, applied in biological neural network models, neural learning methods, neural architectures, etc.
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[0142] exist figure 1 In , an embodiment of the method of predicting a hemodynamic parameter according to the first aspect of the present invention is exemplarily depicted. The method comprises the steps of: receiving 1 a vessel shape model; receiving 2 a corresponding flow distribution; and predicting 3 at least one hemodynamic parameter p k .
[0143] In the step of receiving 1 , a vessel shape model of a target vessel, here exemplarily the aorta of a human subject, is received as a first input. The vessel shape model has been extracted from an image dataset generated by a medical imaging system showing the subject's aorta (eg, a 4D MRI flow dataset generated by a 4D MRI system). The vessel shape model includes a centerline extending from the entrance to the exit of the aorta. The centerline runs through all center points along the aorta. The blood vessel shape model includes a large number of N=100 blood vessel shape points, each of which has a first coordinate in a fir...
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